Generative AI: A Game-Changer in the Security Industry
生成AI：安全行业的游戏改变者

Founders of prominent security startups have recently shed light on the potential impact of generative AI in the tech industry. The discussion took place on the AI + a16z podcast, featuring insights from Dean De Beer of Command Zero, Kevin Tian from Doppel, and Travis McPeak of Resourcely.
著名安全初创公司的创始人最近阐明了生成AI对科技行业的潜在影响。讨论是在AI + A16Z播客上进行的，该播客的见解是Zero的Dean De Beer，Doppel的Kevin Tian和Resourcelly的Travis McPeak。

Building with Large Language Models (LLMs)
使用大型语言模型（LLM）建造

The founders discussed their experiences in dealing with LLM-based threats and building with LLMs. They emphasized the complexity of the process and the multitude of considerations that come into play when choosing and operating a large language model.
创始人讨论了他们在处理基于LLM的威胁和与LLMS建设方面的经验。他们强调了过程的复杂性以及选择和操作大型语言模型时会发挥作用的众多考虑。

LLM Operation: An Intricate Process
LLM操作：一个复杂的过程

De Beer compared the operation of a large language model to perceived waiting time for an elevator. He explained that as the use case becomes more advanced and more data is attached, the inference time changes. Despite the fact that generating an outcome might take longer than the user would prefer, the overall process is still significantly faster than undertaking the task manually.
De Beer将大型语言模型的操作与电梯的等待时间进行了比较。他解释说，随着用例变得更加先进并附加了更多数据，推理时间会改变。尽管产生结果可能要比用户想要的时间更长，但总体过程仍然比手动执行任务要快得多。

Generative AI: A Double-Edged Sword
生成AI：双刃剑

While generative AI offers numerous benefits, it also presents a new set of challenges. These include dealing with threats based on LLMs. However, the founders emphasized that understanding these threats and learning how to manage them is key to leveraging the full potential of generative AI in the security industry.
尽管生成AI提供了许多好处，但它也带来了一系列新的挑战。其中包括处理基于LLM的威胁。但是，创始人强调，了解这些威胁并学习如何管理它们是利用生成AI在安全行业中的全部潜力的关键。